Customers RFM Profiling Report

Dataset statistics

Number of variables	29
Number of observations	3488
Missing cells	228
Missing cells (%)	0.2%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	766.7 KiB
Average record size in memory	225.1 B

Variable types

Numeric	17
Categorical	11
DateTime	1

Alerts

`country` has constant value "Australia"	Constant
`job_title` has a high cardinality: 196 distinct values	High cardinality
`address` has a high cardinality: 3486 distinct values	High cardinality
`df_index` is highly correlated with `customer_id`	High correlation
`customer_id` is highly correlated with `df_index`	High correlation
`past_3_years_bike_related_purchases` is highly correlated with `Frequency` and 5 other fields	High correlation
`tenure` is highly correlated with `age` and 1 other fields	High correlation
`age` is highly correlated with `tenure` and 1 other fields	High correlation
`postcode` is highly correlated with `state` and 1 other fields	High correlation
`property_valuation` is highly correlated with `postcode`	High correlation
`Frequency` is highly correlated with `past_3_years_bike_related_purchases` and 5 other fields	High correlation
`profit` is highly correlated with `M_rank`	High correlation
`Recency` is highly correlated with `R_rank` and 1 other fields	High correlation
`R_rank` is highly correlated with `Recency` and 3 other fields	High correlation
`F_rank` is highly correlated with `past_3_years_bike_related_purchases` and 5 other fields	High correlation
`M_rank` is highly correlated with `profit`	High correlation
`R_rank_norm` is highly correlated with `Recency` and 3 other fields	High correlation
`F_rank_norm` is highly correlated with `past_3_years_bike_related_purchases` and 5 other fields	High correlation
`M_rank_norm` is highly correlated with `past_3_years_bike_related_purchases` and 5 other fields	High correlation
`RFM_Score` is highly correlated with `past_3_years_bike_related_purchases` and 7 other fields	High correlation
`gender` is highly correlated with `job_industry_category` and 1 other fields	High correlation
`job_industry_category` is highly correlated with `gender` and 1 other fields	High correlation
`wealth_segment` is highly correlated with `country`	High correlation
`deceased_indicator` is highly correlated with `country`	High correlation
`owns_car` is highly correlated with `country`	High correlation
`age_group` is highly correlated with `gender` and 3 other fields	High correlation
`state` is highly correlated with `postcode`	High correlation
`country` is highly correlated with `age_group` and 7 other fields	High correlation
`Customer_segment` is highly correlated with `past_3_years_bike_related_purchases` and 7 other fields	High correlation
`DOB` has 76 (2.2%) missing values	Missing
`tenure` has 76 (2.2%) missing values	Missing
`age` has 76 (2.2%) missing values	Missing
`df_index` is uniformly distributed	Uniform
`customer_id` is uniformly distributed	Uniform
`address` is uniformly distributed	Uniform
`M_rank` is uniformly distributed	Uniform
`df_index` has unique values	Unique
`customer_id` has unique values	Unique
`Recency` has 47 (1.3%) zeros	Zeros

Reproduction

Analysis started	2022-12-15 11:22:04.126478
Analysis finished	2022-12-15 11:23:05.721862
Duration	1 minute and 1.6 second
Software version	pandas-profiling v3.4.0
Download configuration	config.json

df_index
Real number (ℝ_≥0)

HIGH CORRELATION
UNIFORM
UNIQUE

Distinct	3488
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1744.491686

Minimum	0
Maximum	3488
Zeros	1
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	27.4 KiB

Quantile statistics

Minimum	0
5-th percentile	175.35
Q1	872.75
median	1744.5
Q3	2616.25
95-th percentile	3313.65
Maximum	3488
Range	3488
Interquartile range (IQR)	1743.5

Descriptive statistics

Standard deviation	1007.057484
Coefficient of variation (CV)	0.5772784656
Kurtosis	-1.199934525
Mean	1744.491686
Median Absolute Deviation (MAD)	872
Skewness	-4.837494574 × 10^-5
Sum	6084787
Variance	1014164.775
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	1	< 0.1%
2330	1	< 0.1%
2319	1	< 0.1%
2320	1	< 0.1%
2321	1	< 0.1%
2322	1	< 0.1%
2323	1	< 0.1%
2324	1	< 0.1%
2325	1	< 0.1%
2326	1	< 0.1%
Other values (3478)	3478	99.7%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	1	< 0.1%
1	1	< 0.1%
2	1	< 0.1%
3	1	< 0.1%
4	1	< 0.1%
5	1	< 0.1%
6	1	< 0.1%
7	1	< 0.1%
8	1	< 0.1%
9	1	< 0.1%

Value	Count	Frequency (%)
3488	1	< 0.1%
3487	1	< 0.1%
3486	1	< 0.1%
3485	1	< 0.1%
3484	1	< 0.1%
3483	1	< 0.1%
3482	1	< 0.1%
3481	1	< 0.1%
3480	1	< 0.1%
3479	1	< 0.1%

customer_id
Real number (ℝ_≥0)

HIGH CORRELATION
UNIFORM
UNIQUE

Distinct	3488
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1752.398222

Minimum	1
Maximum	3500
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.4 KiB

Quantile statistics

Minimum	1
5-th percentile	180.35
Q1	879.75
median	1752.5
Q3	2625.25
95-th percentile	3325.65
Maximum	3500
Range	3499
Interquartile range (IQR)	1745.5

Descriptive statistics

Standard deviation	1009.114046
Coefficient of variation (CV)	0.5758474487
Kurtosis	-1.199495742
Mean	1752.398222
Median Absolute Deviation (MAD)	873
Skewness	-1.87091051 × 10^-5
Sum	6112365
Variance	1018311.157
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	1	< 0.1%
2339	1	< 0.1%
2328	1	< 0.1%
2329	1	< 0.1%
2330	1	< 0.1%
2331	1	< 0.1%
2332	1	< 0.1%
2333	1	< 0.1%
2334	1	< 0.1%
2335	1	< 0.1%
Other values (3478)	3478	99.7%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	1	< 0.1%
2	1	< 0.1%
4	1	< 0.1%
5	1	< 0.1%
6	1	< 0.1%
7	1	< 0.1%
8	1	< 0.1%
9	1	< 0.1%
11	1	< 0.1%
12	1	< 0.1%

Value	Count	Frequency (%)
3500	1	< 0.1%
3499	1	< 0.1%
3498	1	< 0.1%
3497	1	< 0.1%
3496	1	< 0.1%
3495	1	< 0.1%
3494	1	< 0.1%
3493	1	< 0.1%
3492	1	< 0.1%
3491	1	< 0.1%

gender
Categorical

HIGH CORRELATION

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	3.7 KiB

Female	1758
Male	1654
Unknown	76

Length

Max length	7
Median length	6
Mean length	5.073394495
Min length	4

Characters and Unicode

Total characters	17696
Distinct characters	11
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Female
2nd row	Male
3rd row	Male
4th row	Female
5th row	Male

Common Values

Value	Count	Frequency (%)
Female	1758	50.4%
Male	1654	47.4%
Unknown	76	2.2%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
female	1758	50.4%
male	1654	47.4%
unknown	76	2.2%

Most occurring characters

Value	Count	Frequency (%)
e	5170	29.2%
a	3412	19.3%
l	3412	19.3%
F	1758	9.9%
m	1758	9.9%
M	1654	9.3%
n	228	1.3%
U	76	0.4%
k	76	0.4%
o	76	0.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	14208	80.3%
Uppercase Letter	3488	19.7%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	5170	36.4%
a	3412	24.0%
l	3412	24.0%
m	1758	12.4%
n	228	1.6%
k	76	0.5%
o	76	0.5%
w	76	0.5%

Uppercase Letter

Value	Count	Frequency (%)
F	1758	50.4%
M	1654	47.4%
U	76	2.2%

Most occurring scripts

Value	Count	Frequency (%)
Latin	17696	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	5170	29.2%
a	3412	19.3%
l	3412	19.3%
F	1758	9.9%
m	1758	9.9%
M	1654	9.3%
n	228	1.3%
U	76	0.4%
k	76	0.4%
o	76	0.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	17696	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	5170	29.2%
a	3412	19.3%
l	3412	19.3%
F	1758	9.9%
m	1758	9.9%
M	1654	9.3%
n	228	1.3%
U	76	0.4%
k	76	0.4%
o	76	0.4%

past_3_years_bike_related_purchases
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	100
Distinct (%)	2.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	48.79300459

Minimum	0
Maximum	99
Zeros	34
Zeros (%)	1.0%
Negative	0
Negative (%)	0.0%
Memory size	27.4 KiB

Quantile statistics

Minimum	0
5-th percentile	5
Q1	24
median	48
Q3	73
95-th percentile	95
Maximum	99
Range	99
Interquartile range (IQR)	49

Descriptive statistics

Standard deviation	28.61093779
Coefficient of variation (CV)	0.5863737647
Kurtosis	-1.176513967
Mean	48.79300459
Median Absolute Deviation (MAD)	25
Skewness	0.05879815324
Sum	170190
Variance	818.5857612
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
67	50	1.4%
16	50	1.4%
20	49	1.4%
53	47	1.3%
80	46	1.3%
2	44	1.3%
48	44	1.3%
98	44	1.3%
33	43	1.2%
83	42	1.2%
Other values (90)	3029	86.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	34	1.0%
1	28	0.8%
2	44	1.3%
3	24	0.7%
4	32	0.9%
5	27	0.8%
6	41	1.2%
7	32	0.9%
8	22	0.6%
9	36	1.0%

Value	Count	Frequency (%)
99	36	1.0%
98	44	1.3%
97	40	1.1%
96	42	1.2%
95	25	0.7%
94	33	0.9%
93	39	1.1%
92	21	0.6%
91	28	0.8%
90	34	1.0%

DOB
Date

MISSING

Distinct	3046
Distinct (%)	89.3%
Missing	76
Missing (%)	2.2%
Memory size	27.4 KiB

Minimum	1931-10-23 00:00:00
Maximum	2002-03-11 00:00:00

Histogram

Histogram with fixed size bins (bins=50)

job_title
Categorical

HIGH CARDINALITY

Distinct	196
Distinct (%)	5.6%
Missing	0
Missing (%)	0.0%
Memory size	27.4 KiB

Unknown	421
Business Systems Development Analyst	40
Social Worker	38
Tax Accountant	37
Executive Secretary	36
Other values (191)	2916

Length

Max length	36
Median length	26
Mean length	16.87614679
Min length	5

Characters and Unicode

Total characters	58864
Distinct characters	48
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	Executive Secretary
2nd row	Administrative Officer
3rd row	Unknown
4th row	Senior Editor
5th row	Unknown

Common Values

Value	Count	Frequency (%)
Unknown	421	12.1%
Business Systems Development Analyst	40	1.1%
Social Worker	38	1.1%
Tax Accountant	37	1.1%
Executive Secretary	36	1.0%
Internal Auditor	36	1.0%
Legal Assistant	36	1.0%
Associate Professor	35	1.0%
General Manager	35	1.0%
Structural Engineer	34	1.0%
Other values (186)	2740	78.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
engineer	429	5.6%
unknown	421	5.5%
assistant	295	3.9%
manager	241	3.2%
analyst	235	3.1%
iv	198	2.6%
iii	184	2.4%
i	183	2.4%
ii	178	2.3%
systems	156	2.0%
Other values (118)	5110	67.0%

Most occurring characters

Value	Count	Frequency (%)
n	5500	9.3%
e	5471	9.3%
t	4327	7.4%
a	4148	7.0%
	4142	7.0%
i	4061	6.9%
r	3644	6.2%
s	3424	5.8%
o	2977	5.1%
c	2450	4.2%
Other values (38)	18720	31.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	46149	78.4%
Uppercase Letter	8542	14.5%
Space Separator	4142	7.0%
Other Punctuation	31	0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
n	5500	11.9%
e	5471	11.9%
t	4327	9.4%
a	4148	9.0%
i	4061	8.8%
r	3644	7.9%
s	3424	7.4%
o	2977	6.5%
c	2450	5.3%
l	1734	3.8%
Other values (14)	8413	18.2%

Uppercase Letter

Value	Count	Frequency (%)
I	1378	16.1%
A	1259	14.7%
S	990	11.6%
E	636	7.4%
P	606	7.1%
C	443	5.2%
U	421	4.9%
D	419	4.9%
M	389	4.6%
V	341	4.0%
Other values (12)	1660	19.4%

Space Separator

Value	Count	Frequency (%)
	4142	100.0%

Other Punctuation

Value	Count	Frequency (%)
/	31	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	54691	92.9%
Common	4173	7.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
n	5500	10.1%
e	5471	10.0%
t	4327	7.9%
a	4148	7.6%
i	4061	7.4%
r	3644	6.7%
s	3424	6.3%
o	2977	5.4%
c	2450	4.5%
l	1734	3.2%
Other values (36)	16955	31.0%

Common

Value	Count	Frequency (%)
	4142	99.3%
/	31	0.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	58864	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
n	5500	9.3%
e	5471	9.3%
t	4327	7.4%
a	4148	7.0%
	4142	7.0%
i	4061	6.9%
r	3644	6.2%
s	3424	5.8%
o	2977	5.1%
c	2450	4.2%
Other values (38)	18720	31.8%

job_industry_category
Categorical

HIGH CORRELATION

Distinct	10
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Memory size	27.4 KiB

Manufacturing	703
Financial Services	686
Unknown	560
Health	532
Retail	304
Other values (5)	703

Length

Max length	18
Median length	11
Mean length	10.45584862
Min length	2

Characters and Unicode

Total characters	36470
Distinct characters	32
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Health
2nd row	Financial Services
3rd row	IT
4th row	Unknown
5th row	Retail

Common Values

Value	Count	Frequency (%)
Manufacturing	703	20.2%
Financial Services	686	19.7%
Unknown	560	16.1%
Health	532	15.3%
Retail	304	8.7%
Property	230	6.6%
IT	187	5.4%
Entertainment	123	3.5%
Argiculture	100	2.9%
Telecommunications	63	1.8%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
manufacturing	703	16.8%
financial	686	16.4%
services	686	16.4%
unknown	560	13.4%
health	532	12.7%
retail	304	7.3%
property	230	5.5%
it	187	4.5%
entertainment	123	2.9%
argiculture	100	2.4%

Most occurring characters

Value	Count	Frequency (%)
n	4953	13.6%
a	3800	10.4%
i	3414	9.4%
e	2910	8.0%
c	2301	6.3%
t	2301	6.3%
r	2172	6.0%
l	1685	4.6%
u	1669	4.6%
o	916	2.5%
Other values (22)	10349	28.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	31423	86.2%
Uppercase Letter	4361	12.0%
Space Separator	686	1.9%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
n	4953	15.8%
a	3800	12.1%
i	3414	10.9%
e	2910	9.3%
c	2301	7.3%
t	2301	7.3%
r	2172	6.9%
l	1685	5.4%
u	1669	5.3%
o	916	2.9%
Other values (10)	5302	16.9%

Uppercase Letter

Value	Count	Frequency (%)
M	703	16.1%
S	686	15.7%
F	686	15.7%
U	560	12.8%
H	532	12.2%
R	304	7.0%
T	250	5.7%
P	230	5.3%
I	187	4.3%
E	123	2.8%

Space Separator

Value	Count	Frequency (%)
	686	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	35784	98.1%
Common	686	1.9%

Most frequent character per script

Latin

Value	Count	Frequency (%)
n	4953	13.8%
a	3800	10.6%
i	3414	9.5%
e	2910	8.1%
c	2301	6.4%
t	2301	6.4%
r	2172	6.1%
l	1685	4.7%
u	1669	4.7%
o	916	2.6%
Other values (21)	9663	27.0%

Common

Value	Count	Frequency (%)
	686	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	36470	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
n	4953	13.6%
a	3800	10.4%
i	3414	9.4%
e	2910	8.0%
c	2301	6.3%
t	2301	6.3%
r	2172	6.0%
l	1685	4.6%
u	1669	4.6%
o	916	2.5%
Other values (22)	10349	28.4%

wealth_segment
Categorical

HIGH CORRELATION

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.4 KiB

Mass Customer	1744
High Net Worth	894
Affluent Customer	850

Length

Max length	17
Median length	15.5
Mean length	14.23107798
Min length	13

Characters and Unicode

Total characters	49638
Distinct characters	21
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Mass Customer
2nd row	Mass Customer
3rd row	Mass Customer
4th row	Affluent Customer
5th row	High Net Worth

Common Values

Value	Count	Frequency (%)
Mass Customer	1744	50.0%
High Net Worth	894	25.6%
Affluent Customer	850	24.4%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
customer	2594	33.0%
mass	1744	22.2%
high	894	11.4%
net	894	11.4%
worth	894	11.4%
affluent	850	10.8%

Most occurring characters

Value	Count	Frequency (%)
s	6082	12.3%
t	5232	10.5%
	4382	8.8%
e	4338	8.7%
r	3488	7.0%
o	3488	7.0%
u	3444	6.9%
C	2594	5.2%
m	2594	5.2%
h	1788	3.6%
Other values (11)	12208	24.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	37386	75.3%
Uppercase Letter	7870	15.9%
Space Separator	4382	8.8%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
s	6082	16.3%
t	5232	14.0%
e	4338	11.6%
r	3488	9.3%
o	3488	9.3%
u	3444	9.2%
m	2594	6.9%
h	1788	4.8%
a	1744	4.7%
f	1700	4.5%
Other values (4)	3488	9.3%

Uppercase Letter

Value	Count	Frequency (%)
C	2594	33.0%
M	1744	22.2%
H	894	11.4%
N	894	11.4%
W	894	11.4%
A	850	10.8%

Space Separator

Value	Count	Frequency (%)
	4382	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	45256	91.2%
Common	4382	8.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
s	6082	13.4%
t	5232	11.6%
e	4338	9.6%
r	3488	7.7%
o	3488	7.7%
u	3444	7.6%
C	2594	5.7%
m	2594	5.7%
h	1788	4.0%
M	1744	3.9%
Other values (10)	10464	23.1%

Common

Value	Count	Frequency (%)
	4382	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	49638	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
s	6082	12.3%
t	5232	10.5%
	4382	8.8%
e	4338	8.7%
r	3488	7.0%
o	3488	7.0%
u	3444	6.9%
C	2594	5.2%
m	2594	5.2%
h	1788	3.6%
Other values (11)	12208	24.6%

deceased_indicator
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.4 KiB

0	3487
1	1

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	3488
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	0
2nd row	0
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	3487	> 99.9%
1	1	< 0.1%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
0	3487	> 99.9%
1	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	3487	> 99.9%
1	1	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	3488	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	3487	> 99.9%
1	1	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
Common	3488	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	3487	> 99.9%
1	1	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3488	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	3487	> 99.9%
1	1	< 0.1%

owns_car
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.4 KiB

1	1767
0	1721

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	3488
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	0
4th row	1
5th row	1

Common Values

Value	Count	Frequency (%)
1	1767	50.7%
0	1721	49.3%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
1	1767	50.7%
0	1721	49.3%

Most occurring characters

Value	Count	Frequency (%)
1	1767	50.7%
0	1721	49.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	3488	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
1	1767	50.7%
0	1721	49.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	3488	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
1	1767	50.7%
0	1721	49.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3488	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
1	1767	50.7%
0	1721	49.3%

tenure
Real number (ℝ_≥0)

HIGH CORRELATION
MISSING

Distinct	22
Distinct (%)	0.6%
Missing	76
Missing (%)	2.2%
Infinite	0
Infinite (%)	0.0%
Mean	10.67848769

Minimum	1
Maximum	22
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.4 KiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	6
median	11
Q3	15
95-th percentile	20
Maximum	22
Range	21
Interquartile range (IQR)	9

Descriptive statistics

Standard deviation	5.673060209
Coefficient of variation (CV)	0.5312606404
Kurtosis	-1.064779769
Mean	10.67848769
Median Absolute Deviation (MAD)	5
Skewness	0.05121290579
Sum	36435
Variance	32.18361214
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=22)

Value	Count	Frequency (%)
7	203	5.8%
5	195	5.6%
11	193	5.5%
16	188	5.4%
8	184	5.3%
14	183	5.2%
12	178	5.1%
10	177	5.1%
18	175	5.0%
9	174	5.0%
Other values (12)	1562	44.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	148	4.2%
2	130	3.7%
3	142	4.1%
4	168	4.8%
5	195	5.6%
6	162	4.6%
7	203	5.8%
8	184	5.3%
9	174	5.0%
10	177	5.1%

Value	Count	Frequency (%)
22	48	1.4%
21	47	1.3%
20	86	2.5%
19	140	4.0%
18	175	5.0%
17	166	4.8%
16	188	5.4%
15	152	4.4%
14	183	5.2%
13	173	5.0%

age
Real number (ℝ_≥0)

HIGH CORRELATION
MISSING

Distinct	55
Distinct (%)	1.6%
Missing	76
Missing (%)	2.2%
Infinite	0
Infinite (%)	0.0%
Mean	44.82473623

Minimum	20
Maximum	91
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.4 KiB

Quantile statistics

Minimum	20
5-th percentile	24
Q1	35
median	45
Q3	54
95-th percentile	66
Maximum	91
Range	71
Interquartile range (IQR)	19

Descriptive statistics

Standard deviation	12.57954103
Coefficient of variation (CV)	0.2806383728
Kurtosis	-0.7676827226
Mean	44.82473623
Median Absolute Deviation (MAD)	9
Skewness	0.01847513031
Sum	152942
Variance	158.2448526
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
44	187	5.4%
45	181	5.2%
48	135	3.9%
46	134	3.8%
42	114	3.3%
49	108	3.1%
43	107	3.1%
36	99	2.8%
47	97	2.8%
63	87	2.5%
Other values (45)	2163	62.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
20	6	0.2%
21	29	0.8%
22	38	1.1%
23	52	1.5%
24	71	2.0%
25	63	1.8%
26	57	1.6%
27	86	2.5%
28	65	1.9%
29	52	1.5%

Value	Count	Frequency (%)
91	1	< 0.1%
87	1	< 0.1%
82	1	< 0.1%
79	1	< 0.1%
78	1	< 0.1%
69	18	0.5%
68	49	1.4%
67	50	1.4%
66	54	1.5%
65	58	1.7%

age_group
Categorical

HIGH CORRELATION

Distinct	5
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.4 KiB

Gen X (40-54 years)	1465
Millennials (25-39 years)	917
Baby Boomers (55-74 years)	829
Gen Z (10-24 years)	196
Interwar	81

Length

Max length	26
Median length	25
Mean length	21.98566514
Min length	8

Characters and Unicode

Total characters	76686
Distinct characters	31
Distinct categories	7 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Baby Boomers (55-74 years)
2nd row	Gen X (40-54 years)
3rd row	Baby Boomers (55-74 years)
4th row	Gen X (40-54 years)
5th row	Baby Boomers (55-74 years)

Common Values

Value	Count	Frequency (%)
Gen X (40-54 years)	1465	42.0%
Millennials (25-39 years)	917	26.3%
Baby Boomers (55-74 years)	829	23.8%
Gen Z (10-24 years)	196	5.6%
Interwar	81	2.3%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
years	3407	26.6%
gen	1661	13.0%
x	1465	11.5%
40-54	1465	11.5%
millennials	917	7.2%
25-39	917	7.2%
baby	829	6.5%
boomers	829	6.5%
55-74	829	6.5%
z	196	1.5%
Other values (2)	277	2.2%

Most occurring characters

Value	Count	Frequency (%)
	9304	12.1%
e	6895	9.0%
a	5234	6.8%
s	5153	6.7%
r	4398	5.7%
y	4236	5.5%
5	4040	5.3%
4	3955	5.2%
n	3576	4.7%
)	3407	4.4%
Other values (21)	26488	34.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	37555	49.0%
Decimal Number	13628	17.8%
Space Separator	9304	12.1%
Uppercase Letter	5978	7.8%
Close Punctuation	3407	4.4%
Open Punctuation	3407	4.4%
Dash Punctuation	3407	4.4%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	6895	18.4%
a	5234	13.9%
s	5153	13.7%
r	4398	11.7%
y	4236	11.3%
n	3576	9.5%
l	2751	7.3%
i	1834	4.9%
o	1658	4.4%
b	829	2.2%
Other values (3)	991	2.6%

Decimal Number

Value	Count	Frequency (%)
5	4040	29.6%
4	3955	29.0%
0	1661	12.2%
2	1113	8.2%
9	917	6.7%
3	917	6.7%
7	829	6.1%
1	196	1.4%

Uppercase Letter

Value	Count	Frequency (%)
G	1661	27.8%
B	1658	27.7%
X	1465	24.5%
M	917	15.3%
Z	196	3.3%
I	81	1.4%

Space Separator

Value	Count	Frequency (%)
	9304	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	3407	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	3407	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	3407	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	43533	56.8%
Common	33153	43.2%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	6895	15.8%
a	5234	12.0%
s	5153	11.8%
r	4398	10.1%
y	4236	9.7%
n	3576	8.2%
l	2751	6.3%
i	1834	4.2%
G	1661	3.8%
B	1658	3.8%
Other values (9)	6137	14.1%

Common

Value	Count	Frequency (%)
	9304	28.1%
5	4040	12.2%
4	3955	11.9%
)	3407	10.3%
(	3407	10.3%
-	3407	10.3%
0	1661	5.0%
2	1113	3.4%
9	917	2.8%
3	917	2.8%
Other values (2)	1025	3.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	76686	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	9304	12.1%
e	6895	9.0%
a	5234	6.8%
s	5153	6.7%
r	4398	5.7%
y	4236	5.5%
5	4040	5.3%
4	3955	5.2%
n	3576	4.7%
)	3407	4.4%
Other values (21)	26488	34.5%

address
Categorical

HIGH CARDINALITY
UNIFORM

Distinct	3486
Distinct (%)	99.9%
Missing	0
Missing (%)	0.0%
Memory size	27.4 KiB

3 Talisman Place	2
3 Mariners Cove Terrace	2
060 Morning Avenue	1
0 Butterfield Junction	1
6505 Fieldstone Alley	1
Other values (3481)	3481

Length

Max length	29
Median length	25
Mean length	17.68262615
Min length	10

Characters and Unicode

Total characters	61677
Distinct characters	60
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3484 ?
Unique (%)	99.9%

Sample

1st row	060 Morning Avenue
2nd row	6 Meadow Vale Court
3rd row	0 Holy Cross Court
4th row	17979 Del Mar Point
5th row	9 Oakridge Court

Common Values

Value	Count	Frequency (%)
3 Talisman Place	2	0.1%
3 Mariners Cove Terrace	2	0.1%
060 Morning Avenue	1	< 0.1%
0 Butterfield Junction	1	< 0.1%
6505 Fieldstone Alley	1	< 0.1%
5 1st Park	1	< 0.1%
83 American Ash Drive	1	< 0.1%
94 Twin Pines Trail	1	< 0.1%
034 Eagan Avenue	1	< 0.1%
2 Raven Way	1	< 0.1%
Other values (3476)	3476	99.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
crossing	189	1.7%
pass	184	1.7%
center	183	1.7%
court	180	1.7%
circle	179	1.6%
trail	179	1.6%
junction	176	1.6%
place	175	1.6%
street	172	1.6%
lane	172	1.6%
Other values (2505)	9084	83.5%

Most occurring characters

Value	Count	Frequency (%)
	7385	12.0%
e	4978	8.1%
a	4087	6.6%
r	3832	6.2%
n	3090	5.0%
l	2713	4.4%
o	2622	4.3%
i	2589	4.2%
t	2147	3.5%
s	1671	2.7%
Other values (50)	26563	43.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	36457	59.1%
Decimal Number	10500	17.0%
Space Separator	7385	12.0%
Uppercase Letter	7335	11.9%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	4978	13.7%
a	4087	11.2%
r	3832	10.5%
n	3090	8.5%
l	2713	7.4%
o	2622	7.2%
i	2589	7.1%
t	2147	5.9%
s	1671	4.6%
c	1135	3.1%
Other values (16)	7593	20.8%

Uppercase Letter

Value	Count	Frequency (%)
P	1127	15.4%
C	1033	14.1%
S	579	7.9%
A	478	6.5%
T	470	6.4%
M	407	5.5%
L	396	5.4%
H	392	5.3%
D	389	5.3%
R	371	5.1%
Other values (13)	1693	23.1%

Decimal Number

Value	Count	Frequency (%)
3	1099	10.5%
2	1070	10.2%
0	1065	10.1%
8	1060	10.1%
1	1059	10.1%
4	1041	9.9%
5	1038	9.9%
6	1028	9.8%
9	1021	9.7%
7	1019	9.7%

Space Separator

Value	Count	Frequency (%)
	7385	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	43792	71.0%
Common	17885	29.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	4978	11.4%
a	4087	9.3%
r	3832	8.8%
n	3090	7.1%
l	2713	6.2%
o	2622	6.0%
i	2589	5.9%
t	2147	4.9%
s	1671	3.8%
c	1135	2.6%
Other values (39)	14928	34.1%

Common

Value	Count	Frequency (%)
	7385	41.3%
3	1099	6.1%
2	1070	6.0%
0	1065	6.0%
8	1060	5.9%
1	1059	5.9%
4	1041	5.8%
5	1038	5.8%
6	1028	5.7%
9	1021	5.7%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	61677	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	7385	12.0%
e	4978	8.1%
a	4087	6.6%
r	3832	6.2%
n	3090	5.0%
l	2713	4.4%
o	2622	4.3%
i	2589	4.2%
t	2147	3.5%
s	1671	2.7%
Other values (50)	26563	43.1%

postcode
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	835
Distinct (%)	23.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2989.045872

Minimum	2000
Maximum	4883
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.4 KiB

Quantile statistics

Minimum	2000
5-th percentile	2048
Q1	2200
median	2768
Q3	3756.25
95-th percentile	4551
Maximum	4883
Range	2883
Interquartile range (IQR)	1556.25

Descriptive statistics

Standard deviation	852.1480469
Coefficient of variation (CV)	0.285090321
Kurtosis	-0.9290874857
Mean	2989.045872
Median Absolute Deviation (MAD)	598
Skewness	0.6222541559
Sum	10425792
Variance	726156.2939
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2153	28	0.8%
2170	28	0.8%
2145	27	0.8%
2155	26	0.7%
2770	24	0.7%
3977	22	0.6%
2560	20	0.6%
2250	20	0.6%
2065	20	0.6%
2763	19	0.5%
Other values (825)	3254	93.3%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
2000	7	0.2%
2007	2	0.1%
2008	1	< 0.1%
2009	4	0.1%
2010	12	0.3%
2011	2	0.1%
2015	5	0.1%
2016	5	0.1%
2017	5	0.1%
2018	5	0.1%

Value	Count	Frequency (%)
4883	1	< 0.1%
4879	2	0.1%
4878	3	0.1%
4877	1	< 0.1%
4873	3	0.1%
4870	9	0.3%
4869	5	0.1%
4868	3	0.1%
4860	1	< 0.1%
4825	5	0.1%

state
Categorical

HIGH CORRELATION

Distinct	3
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.4 KiB

NSW	1866
VIC	880
QLD	742

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	10464
Distinct characters	9
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	NSW
2nd row	NSW
3rd row	QLD
4th row	NSW
5th row	VIC

Common Values

Value	Count	Frequency (%)
NSW	1866	53.5%
VIC	880	25.2%
QLD	742	21.3%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
nsw	1866	53.5%
vic	880	25.2%
qld	742	21.3%

Most occurring characters

Value	Count	Frequency (%)
N	1866	17.8%
S	1866	17.8%
W	1866	17.8%
V	880	8.4%
I	880	8.4%
C	880	8.4%
Q	742	7.1%
L	742	7.1%
D	742	7.1%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	10464	100.0%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
N	1866	17.8%
S	1866	17.8%
W	1866	17.8%
V	880	8.4%
I	880	8.4%
C	880	8.4%
Q	742	7.1%
L	742	7.1%
D	742	7.1%

Most occurring scripts

Value	Count	Frequency (%)
Latin	10464	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
N	1866	17.8%
S	1866	17.8%
W	1866	17.8%
V	880	8.4%
I	880	8.4%
C	880	8.4%
Q	742	7.1%
L	742	7.1%
D	742	7.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10464	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
N	1866	17.8%
S	1866	17.8%
W	1866	17.8%
V	880	8.4%
I	880	8.4%
C	880	8.4%
Q	742	7.1%
L	742	7.1%
D	742	7.1%

country
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.4 KiB

Australia	3488

Length

Max length	9
Median length	9
Mean length	9
Min length	9

Characters and Unicode

Total characters	31392
Distinct characters	8
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Australia
2nd row	Australia
3rd row	Australia
4th row	Australia
5th row	Australia

Common Values

Value	Count	Frequency (%)
Australia	3488	100.0%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
australia	3488	100.0%

Most occurring characters

Value	Count	Frequency (%)
a	6976	22.2%
A	3488	11.1%
u	3488	11.1%
s	3488	11.1%
t	3488	11.1%
r	3488	11.1%
l	3488	11.1%
i	3488	11.1%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	27904	88.9%
Uppercase Letter	3488	11.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	6976	25.0%
u	3488	12.5%
s	3488	12.5%
t	3488	12.5%
r	3488	12.5%
l	3488	12.5%
i	3488	12.5%

Uppercase Letter

Value	Count	Frequency (%)
A	3488	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	31392	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	6976	22.2%
A	3488	11.1%
u	3488	11.1%
s	3488	11.1%
t	3488	11.1%
r	3488	11.1%
l	3488	11.1%
i	3488	11.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	31392	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	6976	22.2%
A	3488	11.1%
u	3488	11.1%
s	3488	11.1%
t	3488	11.1%
r	3488	11.1%
l	3488	11.1%
i	3488	11.1%

property_valuation
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	12
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	7.515768349

Minimum	1
Maximum	12
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.4 KiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	6
median	8
Q3	10
95-th percentile	11
Maximum	12
Range	11
Interquartile range (IQR)	4

Descriptive statistics

Standard deviation	2.822801011
Coefficient of variation (CV)	0.3755838232
Kurtosis	-0.3251201083
Mean	7.515768349
Median Absolute Deviation (MAD)	2
Skewness	-0.6406124299
Sum	26215
Variance	7.968205547
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=12)

Value	Count	Frequency (%)
9	573	16.4%
8	572	16.4%
10	498	14.3%
7	423	12.1%
11	244	7.0%
6	207	5.9%
5	196	5.6%
4	187	5.4%
12	169	4.8%
3	160	4.6%
Other values (2)	259	7.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	139	4.0%
2	120	3.4%
3	160	4.6%
4	187	5.4%
5	196	5.6%
6	207	5.9%
7	423	12.1%
8	572	16.4%
9	573	16.4%
10	498	14.3%

Value	Count	Frequency (%)
12	169	4.8%
11	244	7.0%
10	498	14.3%
9	573	16.4%
8	572	16.4%
7	423	12.1%
6	207	5.9%
5	196	5.6%
4	187	5.4%
3	160	4.6%

Frequency
Real number (ℝ)

HIGH CORRELATION

Distinct	108
Distinct (%)	3.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	43.12643349

Minimum	-11
Maximum	97
Zeros	30
Zeros (%)	0.9%
Negative	173
Negative (%)	5.0%
Memory size	27.4 KiB

Quantile statistics

Minimum	-11
5-th percentile	0
Q1	18
median	42
Q3	68
95-th percentile	89
Maximum	97
Range	108
Interquartile range (IQR)	50

Descriptive statistics

Standard deviation	28.70681501
Coefficient of variation (CV)	0.6656431495
Kurtosis	-1.16093077
Mean	43.12643349
Median Absolute Deviation (MAD)	24
Skewness	0.05723707919
Sum	150425
Variance	824.0812282
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
65	51	1.5%
33	51	1.5%
61	48	1.4%
18	48	1.4%
69	46	1.3%
62	46	1.3%
41	46	1.3%
11	45	1.3%
8	44	1.3%
30	44	1.3%
Other values (98)	3019	86.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
-11	2	0.1%
-9	6	0.2%
-8	10	0.3%
-7	13	0.4%
-6	17	0.5%
-5	20	0.6%
-4	20	0.6%
-3	32	0.9%
-2	25	0.7%
-1	28	0.8%

Value	Count	Frequency (%)
97	2	0.1%
96	5	0.1%
95	11	0.3%
94	22	0.6%
93	28	0.8%
92	36	1.0%
91	44	1.3%
90	21	0.6%
89	32	0.9%
88	29	0.8%

profit
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	3391
Distinct (%)	97.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3127.561411

Minimum	15.1
Maximum	11668.9
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.4 KiB

Quantile statistics

Minimum	15.1
5-th percentile	641.145
Q1	1841.175
median	2859.75
Q3	4179.875
95-th percentile	6365.295
Maximum	11668.9
Range	11653.8
Interquartile range (IQR)	2338.7

Descriptive statistics

Standard deviation	1770.695072
Coefficient of variation (CV)	0.5661583707
Kurtosis	0.7957856964
Mean	3127.561411
Median Absolute Deviation (MAD)	1131.2
Skewness	0.778913283
Sum	10908934.2
Variance	3135361.039
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2795.8	3	0.1%
2073.8	2	0.1%
3660.5	2	0.1%
2500.3	2	0.1%
2344	2	0.1%
3081.1	2	0.1%
4965.7	2	0.1%
1924.2	2	0.1%
299.3	2	0.1%
4557.6	2	0.1%
Other values (3381)	3467	99.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
15.1	1	< 0.1%
17.9	1	< 0.1%
35.7	1	< 0.1%
41.1	2	0.1%
50.2	1	< 0.1%
50.7	1	< 0.1%
57.7	1	< 0.1%
63.8	1	< 0.1%
64.5	1	< 0.1%
75.5	1	< 0.1%

Value	Count	Frequency (%)
11668.9	1	< 0.1%
11222.6	1	< 0.1%
10787.6	1	< 0.1%
10640.3	1	< 0.1%
10497.8	1	< 0.1%
10422	1	< 0.1%
10341.6	1	< 0.1%
10028.8	1	< 0.1%
9739.5	1	< 0.1%
9695.6	1	< 0.1%

Recency
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	280
Distinct (%)	8.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	61.36353211

Minimum	0
Maximum	353
Zeros	47
Zeros (%)	1.3%
Negative	0
Negative (%)	0.0%
Memory size	27.4 KiB

Quantile statistics

Minimum	0
5-th percentile	3
Q1	17
median	44
Q3	86
95-th percentile	181
Maximum	353
Range	353
Interquartile range (IQR)	69

Descriptive statistics

Standard deviation	58.41284552
Coefficient of variation (CV)	0.9519146554
Kurtosis	2.720416376
Mean	61.36353211
Median Absolute Deviation (MAD)	31
Skewness	1.570525691
Sum	214036
Variance	3412.060522
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
11	60	1.7%
14	57	1.6%
2	55	1.6%
12	53	1.5%
1	51	1.5%
4	51	1.5%
5	51	1.5%
24	51	1.5%
8	50	1.4%
17	49	1.4%
Other values (270)	2960	84.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	47	1.3%
1	51	1.5%
2	55	1.6%
3	49	1.4%
4	51	1.5%
5	51	1.5%
6	42	1.2%
7	42	1.2%
8	50	1.4%
9	47	1.3%

Value	Count	Frequency (%)
353	1	< 0.1%
338	1	< 0.1%
333	1	< 0.1%
329	1	< 0.1%
328	1	< 0.1%
325	1	< 0.1%
321	1	< 0.1%
315	1	< 0.1%
312	1	< 0.1%
308	1	< 0.1%

R_rank
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	280
Distinct (%)	8.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1745.308343

Minimum	1
Maximum	3466
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.4 KiB

Quantile statistics

Minimum	1
5-th percentile	176
Q1	869
median	1744
Q3	2635
95-th percentile	3312
Maximum	3466
Range	3465
Interquartile range (IQR)	1766

Descriptive statistics

Standard deviation	1007.26688
Coefficient of variation (CV)	0.5771283247
Kurtosis	-1.199998587
Mean	1745.308343
Median Absolute Deviation (MAD)	875
Skewness	-0.0007882302217
Sum	6087635.5
Variance	1014586.568
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2927.5	60	1.7%
2771	57	1.6%
3364	55	1.6%
2871	53	1.5%
3417	51	1.5%
3262	51	1.5%
3211	51	1.5%
2369	51	1.5%
3076.5	50	1.4%
2635	49	1.4%
Other values (270)	2960	84.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	1	< 0.1%
2	1	< 0.1%
3	1	< 0.1%
4	1	< 0.1%
5	1	< 0.1%
6	1	< 0.1%
7	1	< 0.1%
8	1	< 0.1%
9	1	< 0.1%
10	1	< 0.1%

Value	Count	Frequency (%)
3466	47	1.3%
3417	51	1.5%
3364	55	1.6%
3312	49	1.4%
3262	51	1.5%
3211	51	1.5%
3164.5	42	1.2%
3122.5	42	1.2%
3076.5	50	1.4%
3028	47	1.3%

F_rank
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	108
Distinct (%)	3.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1744.912701

Minimum	1.5
Maximum	3488.5
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.4 KiB

Quantile statistics

Minimum	1.5
5-th percentile	188.5
Q1	870.5
median	1744.5
Q3	2633
95-th percentile	3304.5
Maximum	3488.5
Range	3487
Interquartile range (IQR)	1762.5

Descriptive statistics

Standard deviation	1007.409204
Coefficient of variation (CV)	0.5773407483
Kurtosis	-1.200605693
Mean	1744.912701
Median Absolute Deviation (MAD)	874
Skewness	0.0002645725479
Sum	6086255.5
Variance	1014873.305
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2535	51	1.5%
1406	51	1.5%
2363.5	48	1.4%
870.5	48	1.4%
2673.5	46	1.3%
2410.5	46	1.3%
1705.5	46	1.3%
596	45	1.3%
484.5	44	1.3%
1286.5	44	1.3%
Other values (98)	3019	86.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1.5	2	0.1%
5.5	6	0.2%
13.5	10	0.3%
25	13	0.4%
40	17	0.5%
58.5	20	0.6%
78.5	20	0.6%
104.5	32	0.9%
133	25	0.7%
159.5	28	0.8%

Value	Count	Frequency (%)
3488.5	2	0.1%
3485	5	0.1%
3477	11	0.3%
3460.5	22	0.6%
3435.5	28	0.8%
3403.5	36	1.0%
3363.5	44	1.3%
3331	21	0.6%
3304.5	32	0.9%
3274	29	0.8%

M_rank
Real number (ℝ_≥0)

HIGH CORRELATION
UNIFORM

Distinct	3470
Distinct (%)	99.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1744.664851

Minimum	1
Maximum	3489
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.4 KiB

Quantile statistics

Minimum	1
5-th percentile	175.35
Q1	872.75
median	1744.5
Q3	2616.25
95-th percentile	3314.65
Maximum	3489
Range	3488
Interquartile range (IQR)	1743.5

Descriptive statistics

Standard deviation	1007.28173
Coefficient of variation (CV)	0.577349701
Kurtosis	-1.199644951
Mean	1744.664851
Median Absolute Deviation (MAD)	872
Skewness	0.0005502358331
Sum	6085391
Variance	1014616.484
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
52.5	2	0.1%
44.5	2	0.1%
4.5	2	0.1%
196.5	2	0.1%
391.5	2	0.1%
95.5	2	0.1%
126.5	2	0.1%
80.5	2	0.1%
75.5	2	0.1%
698.5	2	0.1%
Other values (3460)	3468	99.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	1	< 0.1%
2	1	< 0.1%
3	1	< 0.1%
4.5	2	0.1%
6	1	< 0.1%
7	1	< 0.1%
8	1	< 0.1%
9	1	< 0.1%
10	1	< 0.1%
11	1	< 0.1%

Value	Count	Frequency (%)
3489	1	< 0.1%
3488	1	< 0.1%
3487	1	< 0.1%
3486	1	< 0.1%
3485	1	< 0.1%
3484	1	< 0.1%
3483	1	< 0.1%
3482	1	< 0.1%
3481	1	< 0.1%
3480	1	< 0.1%

R_rank_norm
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	228
Distinct (%)	6.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	50.35699541

Minimum	0
Maximum	100
Zeros	1
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	27.4 KiB

Quantile statistics

Minimum	0
5-th percentile	5.1
Q1	25.1
median	50.3
Q3	76
95-th percentile	95.6
Maximum	100
Range	100
Interquartile range (IQR)	50.9

Descriptive statistics

Standard deviation	29.06136437
Coefficient of variation (CV)	0.5771067978
Kurtosis	-1.199520715
Mean	50.35699541
Median Absolute Deviation (MAD)	25.2
Skewness	-0.0007491943219
Sum	175645.2
Variance	844.5628991
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
84.5	60	1.7%
79.9	57	1.6%
97.1	55	1.6%
82.8	53	1.5%
94.1	51	1.5%
68.3	51	1.5%
92.6	51	1.5%
98.6	51	1.5%
88.8	50	1.4%
76	49	1.4%
Other values (218)	2960	84.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	1	< 0.1%
0.1	4	0.1%
0.2	3	0.1%
0.3	4	0.1%
0.4	4	0.1%
0.5	3	0.1%
0.6	3	0.1%
0.7	3	0.1%
0.8	4	0.1%
0.9	3	0.1%

Value	Count	Frequency (%)
100	47	1.3%
98.6	51	1.5%
97.1	55	1.6%
95.6	49	1.4%
94.1	51	1.5%
92.6	51	1.5%
91.3	42	1.2%
90.1	42	1.2%
88.8	50	1.4%
87.4	47	1.3%

F_rank_norm
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	108
Distinct (%)	3.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	50.02462729

Minimum	0
Maximum	100
Zeros	2
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	27.4 KiB

Quantile statistics

Minimum	0
5-th percentile	5.4
Q1	25
median	50
Q3	75.5
95-th percentile	94.7
Maximum	100
Range	100
Interquartile range (IQR)	50.5

Descriptive statistics

Standard deviation	28.8760021
Coefficient of variation (CV)	0.5772357269
Kurtosis	-1.200430976
Mean	50.02462729
Median Absolute Deviation (MAD)	25
Skewness	3.903813219 × 10^-5
Sum	174485.9
Variance	833.8234971
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
72.7	51	1.5%
40.3	51	1.5%
67.8	48	1.4%
25	48	1.4%
76.6	46	1.3%
69.1	46	1.3%
48.9	46	1.3%
17.1	45	1.3%
13.9	44	1.3%
36.9	44	1.3%
Other values (98)	3019	86.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	2	0.1%
0.2	6	0.2%
0.4	10	0.3%
0.7	13	0.4%
1.1	17	0.5%
1.7	20	0.6%
2.3	20	0.6%
3	32	0.9%
3.8	25	0.7%
4.6	28	0.8%

Value	Count	Frequency (%)
100	2	0.1%
99.9	5	0.1%
99.7	11	0.3%
99.2	22	0.6%
98.5	28	0.8%
97.6	36	1.0%
96.4	44	1.3%
95.5	21	0.6%
94.7	32	0.9%
93.9	29	0.8%

M_rank_norm
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	108
Distinct (%)	3.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	50.01356078

Minimum	0
Maximum	100
Zeros	2
Zeros (%)	0.1%
Negative	0
Negative (%)	0.0%
Memory size	27.4 KiB

Quantile statistics

Minimum	0
5-th percentile	5.4
Q1	24.9
median	50
Q3	75.5
95-th percentile	94.7
Maximum	100
Range	100
Interquartile range (IQR)	50.6

Descriptive statistics

Standard deviation	28.87180962
Coefficient of variation (CV)	0.5772796251
Kurtosis	-1.200440031
Mean	50.01356078
Median Absolute Deviation (MAD)	25.1
Skewness	4.213769777 × 10^-5
Sum	174447.3
Variance	833.5813905
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
72.7	51	1.5%
40.3	51	1.5%
67.7	48	1.4%
24.9	48	1.4%
76.6	46	1.3%
69.1	46	1.3%
48.9	46	1.3%
17.1	45	1.3%
13.9	44	1.3%
36.9	44	1.3%
Other values (98)	3019	86.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	2	0.1%
0.2	6	0.2%
0.4	10	0.3%
0.7	13	0.4%
1.1	17	0.5%
1.7	20	0.6%
2.2	20	0.6%
3	32	0.9%
3.8	25	0.7%
4.6	28	0.8%

Value	Count	Frequency (%)
100	2	0.1%
99.9	5	0.1%
99.7	11	0.3%
99.2	22	0.6%
98.5	28	0.8%
97.5	36	1.0%
96.4	44	1.3%
95.5	21	0.6%
94.7	32	0.9%
93.8	29	0.8%

RFM_Score
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	49
Distinct (%)	1.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.506450688

Minimum	0.1
Maximum	4.9
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	27.4 KiB

Quantile statistics

Minimum	0.1
5-th percentile	0.8
Q1	1.7
median	2.5
Q3	3.3
95-th percentile	4.2
Maximum	4.9
Range	4.8
Interquartile range (IQR)	1.6

Descriptive statistics

Standard deviation	1.069541398
Coefficient of variation (CV)	0.4267155156
Kurtosis	-0.8591577538
Mean	2.506450688
Median Absolute Deviation (MAD)	0.8
Skewness	-0.004783144915
Sum	8742.5
Variance	1.143918801
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=49)

Value	Count	Frequency (%)
3.1	123	3.5%
2.1	114	3.3%
3.3	114	3.3%
2.9	111	3.2%
2.6	111	3.2%
3.5	111	3.2%
2.4	110	3.2%
1.8	107	3.1%
3	106	3.0%
1.6	104	3.0%
Other values (39)	2377	68.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.1	4	0.1%
0.2	6	0.2%
0.3	16	0.5%
0.4	25	0.7%
0.5	28	0.8%
0.6	37	1.1%
0.7	44	1.3%
0.8	57	1.6%
0.9	59	1.7%
1	60	1.7%

Value	Count	Frequency (%)
4.9	6	0.2%
4.8	15	0.4%
4.7	19	0.5%
4.6	14	0.4%
4.5	29	0.8%
4.4	42	1.2%
4.3	48	1.4%
4.2	50	1.4%
4.1	53	1.5%
4	65	1.9%

Customer_segment
Categorical

HIGH CORRELATION

Distinct	5
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	27.4 KiB

Low Value	1425
Medium Value	918
Inactive	869
High value	222
Top	54

Length

Max length	12
Median length	10
Mean length	9.511181193
Min length	3

Characters and Unicode

Total characters	33175
Distinct characters	23
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	High value
2nd row	Medium Value
3rd row	Inactive
4th row	Medium Value
5th row	Low Value

Common Values

Value	Count	Frequency (%)
Low Value	1425	40.9%
Medium Value	918	26.3%
Inactive	869	24.9%
High value	222	6.4%
Top	54	1.5%

Length

Histogram of lengths of the category

Category Frequency Plot

Value	Count	Frequency (%)
value	2565	42.4%
low	1425	23.5%
medium	918	15.2%
inactive	869	14.4%
high	222	3.7%
top	54	0.9%

Most occurring characters

Value	Count	Frequency (%)
e	4352	13.1%
u	3483	10.5%
a	3434	10.4%
	2565	7.7%
l	2565	7.7%
V	2343	7.1%
i	2009	6.1%
o	1479	4.5%
L	1425	4.3%
w	1425	4.3%
Other values (13)	8095	24.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	24779	74.7%
Uppercase Letter	5831	17.6%
Space Separator	2565	7.7%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	4352	17.6%
u	3483	14.1%
a	3434	13.9%
l	2565	10.4%
i	2009	8.1%
o	1479	6.0%
w	1425	5.8%
v	1091	4.4%
d	918	3.7%
m	918	3.7%
Other values (6)	3105	12.5%

Uppercase Letter

Value	Count	Frequency (%)
V	2343	40.2%
L	1425	24.4%
M	918	15.7%
I	869	14.9%
H	222	3.8%
T	54	0.9%

Space Separator

Value	Count	Frequency (%)
	2565	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	30610	92.3%
Common	2565	7.7%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	4352	14.2%
u	3483	11.4%
a	3434	11.2%
l	2565	8.4%
V	2343	7.7%
i	2009	6.6%
o	1479	4.8%
L	1425	4.7%
w	1425	4.7%
v	1091	3.6%
Other values (12)	7004	22.9%

Common

Value	Count	Frequency (%)
	2565	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	33175	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	4352	13.1%
u	3483	10.5%
a	3434	10.4%
	2565	7.7%
l	2565	7.7%
V	2343	7.1%
i	2009	6.1%
o	1479	4.5%
L	1425	4.3%
w	1425	4.3%
Other values (13)	8095	24.4%

Auto

The auto setting is an easily interpretable pairwise column metric of the following mapping: vartype-vartype : method, categorical-categorical : Cramer's V, numerical-categorical : Cramer's V (using a discretized numerical column), numerical-numerical : Spearman's ρ. This configuration uses the best suitable for each pair of columns.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	df_index	customer_id	gender	past_3_years_bike_related_purchases	DOB	job_title	job_industry_category	wealth_segment	owns_car	tenure	age	age_group	address	postcode	state	country	property_valuation	Frequency	profit	Recency	R_rank	F_rank	M_rank	R_rank_norm	F_rank_norm	M_rank_norm	RFM_Score	Customer_segment
0	0	1	Female	93	1953-10-12	Executive Secretary	Health	Mass Customer	1	11.0	69.0	Baby Boomers (55-74 years)	060 Morning Avenue	2016	NSW	Australia	10	82	3018.1	7	3122.5	3097.5	1857.0	90.1	88.8	88.8	4.5	High value
1	1	2	Male	81	1980-12-16	Administrative Officer	Financial Services	Mass Customer	1	16.0	42.0	Gen X (40-54 years)	6 Meadow Vale Court	2153	NSW	Australia	10	78	2226.3	128	457.5	2973.0	1187.0	13.2	85.2	85.2	3.1	Medium Value
2	2	4	Male	33	1961-10-03	Unknown	IT	Mass Customer	0	7.0	61.0	Baby Boomers (55-74 years)	0 Holy Cross Court	4211	QLD	Australia	9	31	220.6	195	137.5	1327.0	55.0	4.0	38.0	38.0	1.3	Inactive
3	3	5	Female	56	1977-05-13	Senior Editor	Unknown	Affluent Customer	1	8.0	45.0	Gen X (40-54 years)	17979 Del Mar Point	2448	NSW	Australia	4	50	2394.9	16	2684.0	2013.0	1336.0	77.4	57.7	57.7	3.2	Medium Value
4	4	6	Male	35	1966-09-16	Unknown	Retail	High Net Worth	1	13.0	56.0	Baby Boomers (55-74 years)	9 Oakridge Court	3216	VIC	Australia	9	30	3946.6	64	1263.5	1286.5	2491.0	36.5	36.9	36.9	1.8	Low Value
5	5	7	Female	6	1976-02-23	Unknown	Financial Services	Affluent Customer	1	11.0	46.0	Gen X (40-54 years)	4 Delaware Trail	2210	NSW	Australia	9	3	220.1	253	50.0	302.5	54.0	1.4	8.7	8.7	0.3	Inactive
6	6	8	Male	31	1962-03-30	Media Manager I	Unknown	Mass Customer	0	7.0	60.0	Baby Boomers (55-74 years)	49 Londonderry Lane	2650	NSW	Australia	4	21	7066.9	22	2440.5	974.0	3395.0	70.4	27.9	27.9	2.1	Low Value
7	7	9	Female	97	1973-03-10	Business Systems Development Analyst	Argiculture	Affluent Customer	1	8.0	49.0	Gen X (40-54 years)	97736 7th Trail	2023	NSW	Australia	12	91	2353.1	78	1003.5	3363.5	1309.0	29.0	96.4	96.4	3.7	Medium Value
8	8	11	Male	99	1954-04-30	Unknown	Property	Mass Customer	0	9.0	68.0	Baby Boomers (55-74 years)	93405 Ludington Park	3044	VIC	Australia	8	93	3638.8	46	1686.0	3435.5	2299.0	48.6	98.5	98.5	4.1	High value
9	9	12	Male	58	1994-07-21	Nuclear Power Engineer	Manufacturing	Mass Customer	0	8.0	28.0	Millennials (25-39 years)	44339 Golden Leaf Alley	4557	QLD	Australia	4	51	3540.0	67	1205.0	2049.5	2226.0	34.8	58.8	58.7	2.5	Low Value

Last rows

	df_index	customer_id	gender	past_3_years_bike_related_purchases	DOB	job_title	job_industry_category	wealth_segment	owns_car	tenure	age	age_group	address	postcode	state	country	property_valuation	Frequency	profit	Recency	R_rank	F_rank	M_rank	R_rank_norm	F_rank_norm	M_rank_norm	RFM_Score	Customer_segment
3478	3479	3491	Female	69	1976-04-03	Business Systems Development Analyst	Financial Services	Affluent Customer	0	10.0	46.0	Gen X (40-54 years)	82 Dahle Crossing	3195	VIC	Australia	10	65	1430.3	189	150.5	2535.0	583.0	4.3	72.7	72.7	2.5	Low Value
3479	3480	3492	Male	83	1966-01-27	Civil Engineer	Manufacturing	Mass Customer	0	19.0	56.0	Baby Boomers (55-74 years)	2986 Holmberg Circle	3021	VIC	Australia	9	80	2193.8	80	969.5	3034.0	1155.0	28.0	87.0	87.0	3.4	Medium Value
3480	3481	3493	Male	30	1964-02-29	Research Assistant I	Health	High Net Worth	0	18.0	58.0	Baby Boomers (55-74 years)	3 Monument Crossing	2090	NSW	Australia	10	24	3728.9	93	777.5	1072.5	2362.0	22.4	30.7	30.7	1.4	Inactive
3481	3482	3494	Male	72	1998-12-24	Account Representative IV	Argiculture	High Net Worth	0	1.0	24.0	Gen Z (10-24 years)	35 Chive Alley	2033	NSW	Australia	10	68	2755.1	4	3262.0	2633.0	1656.0	94.1	75.5	75.5	4.1	High value
3482	3483	3495	Female	57	1987-07-12	Programmer III	Financial Services	High Net Worth	0	8.0	35.0	Millennials (25-39 years)	1 Dayton Park	2767	NSW	Australia	9	50	3847.6	13	2822.0	2013.0	2429.0	81.4	57.7	57.7	3.3	Medium Value
3483	3484	3496	Male	99	1986-04-25	Editor	Manufacturing	Mass Customer	1	19.0	36.0	Millennials (25-39 years)	2565 Caliangt Point	2171	NSW	Australia	9	95	2045.8	256	46.0	3477.0	1010.0	1.3	99.7	99.7	3.4	Medium Value
3484	3485	3497	Female	73	1986-05-03	Administrative Assistant IV	Manufacturing	Affluent Customer	1	18.0	36.0	Millennials (25-39 years)	96 Delladonna Trail	3976	VIC	Australia	5	70	1648.3	52	1544.0	2715.0	719.0	44.5	77.8	77.8	3.3	Medium Value
3485	3486	3498	Female	28	1995-11-02	Unknown	Manufacturing	Mass Customer	0	5.0	27.0	Millennials (25-39 years)	3 Nova Point	3012	VIC	Australia	4	22	3147.3	127	462.5	1007.5	1943.0	13.3	28.9	28.9	1.2	Inactive
3486	3487	3499	Male	29	1979-06-17	Unknown	Manufacturing	Mass Customer	1	7.0	43.0	Gen X (40-54 years)	310 Stephen Terrace	4073	QLD	Australia	9	22	4955.2	51	1566.5	1007.5	2968.0	45.2	28.9	28.9	1.7	Low Value
3487	3488	3500	Female	71	1967-07-21	Unknown	Entertainment	Affluent Customer	0	17.0	55.0	Baby Boomers (55-74 years)	9491 Green Ridge Terrace	2100	NSW	Australia	10	65	1785.9	144	338.0	2535.0	822.0	9.8	72.7	72.7	2.6	Low Value

Overview

Variables

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Most occurring scripts

Most frequent character per script

Latin

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Other Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Category Frequency Plot